Causal Learning for Partially Observed Stochastic Dynamical Systems

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Causal Models for Dynamical Systems (2020, neutral): “For speciﬁc model classes, there is interesting work exploiting the concept of local independence [Schweder, 1970, Mogensen et al., 2018, Mogensen and Hansen, 2019, Didelez, 2000, 2008], with several questions still being open.”
Foundations of structural causal models with cycles and latent variables (2016, background): “However, causal cycles may arise when one approximates such systems over time [16, 39, 40] or when one describes the equilibrium states of these systems [3, 5, 24, 26, 30, 43, 53].”
Markov equivalence of marginalized local independence graphs (2018, background): “Moreover, general sufﬁcient conditions for the global Markov property were given in [30] covering point processes as well as certain diffusion processes.”